Real-time recommendation engines are key to the success of any online business. To make relevant recommendations in real time requires the ability to correlate product, customer, inventory, supplier, logistics and even social sentiment data. Moreover, a real-time recommendation engine requires the ability to instantly capture any new interests shown in the customer’s’ current visit – something that batch processing can’t accomplish. Matching historical and session data is trivial for a graph database like Neo4j.
The key technology in enabling real-time recommendations is the graph database, a technology that is fast leaving traditional relational databases behind. Graph databases easily outperform relational and other NoSQL data stores for connecting masses of buyer and product data (and connected data in general) to gain insight into customer needs and product trends. https://neo4j.com/real-time-recommendation-engines-a/
Here a example of friendship recommendation on Neo4j in Naruto universe.